가변구조 제어시스템의 Luenberger Observer에 관한 연구

탁한호,이형기,박양수,권세현 釜山工業大學校 1991 論文集 Vol.33 No.-

This paper presents an analysis of the stste observer-based robust speed control of a self-controlled synchonous motor (SCSM). A Variable structure control (VSC) technique is utilized to achieve robust (paramater-insensitive) characteristics. The speed and acceleration signals required for the implementation of the variable structure speed control (VSSC) are dynamically estimated with stste observer. One kind observer-the Luenberger full order observer-air explored in this paper. The results obtained that Luenverger observers do estimate the system ststes accurately when the system parameters vary. The design methods and the simulation results presented demonstrable the potential of the proposed scheme.

DC 전동기 제어를 위한 뉴로-퍼지 적응제어기의 설계

탁한호,김명규 진주산업대학교 1999 論文集 Vol.38 No.-

This paper aims at finding out an efficient method to control a DC Motor using Neuro-Fuzzy Adaptive Controller(NFAC). Generally parameters or operating conditions of DC Motor controllers are uncertain or unknown compared with the case of PID controller. PID controller, however, does not guarantee a good performance, which is possible only with precisely known system parameters and operating conditions. It is difficult to control an unstable nonlinear control system. Fuzzy theory has been effectively applied to this system. But it is difficult to exactly design the fuzzy controller, because membership functions and rules of a fuzzy controller are not always available. The proposed adaptive structure of the fuzzy reasoning system can be controlled more adaptively and effectively in nonlinear environment by changing input and output membership functions. The proposed fuzzy inference algorithm is named NFAC. The NFAC performance is more effective than that of the PID in the convergence time. Compared with PID, it provides an improved performance.

신경망을 이용한 회전 역진자 시스템의 제어

탁한호,이주원,신춘식 진주산업대학교 1997 論文集 Vol.36 No.-

Today, the complexity and nonlinearity in system have increased. For example, an inverted pendulum of nonlinear system is widely used as a substitute of nonlinear control system. But it is difficult to establish mathemathical equation and model control system. This paper aims to propose a method to control desired position and desired pole angle of the rotary inverted pendulum using multilayer neural networks. In the begining of learning, we controller the system using PD controller to avoid unstability of system. After learning of neural networks we controlled the system using neural networks. In this paper we compare the result of PD controller with result of neural networks, and point out some good points of neural networks for nonlinear system control.

모델기준 적응제어 보상기와 Sliding Mode 기법을 이용한 DC Servo Motor 위치제어의 응답특성

卓漢浩 진주산업대학교 농업기술연구소 1991 農業技術硏究所報 Vol.4 No.-

The sliding mode control in an effective mehtode to establish robustness against parameter variation and disterbance. But, In sliding mode strategy, the control function is discontinuous on the hyperplane. However the discontinuous change in control structure caves the controller input to chaffer and gives non-zero steady state error. Consequently, a multiloop feedback control system supplemented by a complementary controller is used to improved the drive performance of a DC servo motor and reduce sensitivity to parameter variation, nonlinear effects, and other disturbances.

회전 역진자의 위치제어를 위한 적응 퍼지-신경망 제어기의 설계

탁한호,추연규 진주산업대학교 농업기술연구소 2000 農業技術硏究所報 Vol.13 No.-

In this paper, an position control method using adaptive fuzzy-neural controller(AFNC) is proposed for modeling of nonlinear complex systems. The proposed adaptive fuzzy-neural controller implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks from input and output data of processes. Inference type for this adaptive fuzzy-neural controller is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of adaptive fuzzy-neural controller are tuned automatically using improved modified complex method and modified leaning algorithm. For the purpose of its application to nonlinear processes, data for rotating inverted pendulum system ar used for the purpose of evaluating the performance of the proposed adaptive fuzzy-neural controller. The results show that the proposed method can produce the intelligence model with higher accuracy than other works achieved previously.

PID 제어기의 퍼지 이득 조정

탁한호,추연규,김현덕 진주산업대학교 1999 산업과학기술연구소보 Vol.- No.6

The purpose of this paper is to find PID parameters. The model of controller is designed by Matlab-Simulink program and each parameter of PID is estimated automatically by the Fuzzy controller. The simulation is carried out on FGS(Fuzzy Gain Scheduling), and then this is compared and analyzed with the simple PID controller.

유연한 로보트 매니퓰레이터의 위치제어에 관한 연구

卓漢浩,李寅龍 진주산업대학교 1996 論文集 Vol.35 No.-

In this paper, applications of the multilayer neural networks to the control of flexible robot manipulators are considered. The multilayer neural network can be used to aproximate any continuous function to any desired degree of accuracy and the weights are updaed by Gradient Method. When the flexible manipulator is rotated by motor through the fixed end, the transverse vibration may occur. The motor torque should be controlled in such a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipulators so that it is arrested as soon as possible at the end of rotation. Accurate control of lightweight manipulators during the large changes in configuration common to robotic tasks requires dynamic models that describe both the rigidbody motions, and the flexural vibrations. Therefore, this paper derives a linear dynamic state-space model for a single link flexible robot manipulator and composed LQR controller and inverse dynamical neuro-controller. The effectiveness of the proposed control system was proved by computer simulation.

퍼지 논리에 의한 칼만 필터의 파라메터 조정기 설계

탁한호,추연규 진주산업대학교 농업기술연구소 1998 農業技術硏究所報 Vol.11 No.-

칼만 필터는 피드백 제어의 형태를 사용하는 플랜트를 추정한다. 플랜트의 잡음이나 측정 외란이 발생하더라도 상태를 추정하여 최적의 제어를 행한다. 상태를 추정하기 위하여 칼만 필터의 이득 K_k를 조절하였고, 이 이득은 칼만 필터의 파라메터인 측정 오차 공분산 R_k과 프로세서 잡음 오차 공분산 Q_k를 오프-라인에서 조정함으로써 뛰어난 필터 수행을 얻을 수 있다. 그러나 필터 파라메터 R_k, Q_k는 필터 연산 이전에 측정되어야 하지만, 현재는 전문가가 전문적인 지식을 바탕으로 파라메터를 조정하여 시스템을 제어하고 있다. 따라서 이러한 비효율적인 작업을 퍼지 논리 제어기를 이용하여 오프-라인에서 최적의 파라메터 R_k를 구하고자 한다. In this paper, an parameter regulator of Kalman filter for nonlinear processes using fuzzy logic is proposed. Kalman filter estimate plant from type of feedback control. The proposed parameter regulator of Kalman filter estimate nonlinear process well due to the intrinsic nonlinearity of the fuzzy logic.

보상형 퍼지 제어기 설계에 관한 연구

탁한호,추연규 진주산업대학교 2000 산업과학기술연구소보 Vol.- No.7

FLC(Fuzzy Logic Controller) is stronger to the disturbance than a classical controller and its overshoot of the intialized value is excellent. In case an unknown process or the mathematical modeling of a complicated system is impossible, a fit control quantity can be acquired by the fuzzy inference, But FLC is not able to adjust the rule-base with respect to any sudden changes of the control environment. There are many ways to overcome the problems, but we will propose CFLC(Compensated Fuzzy Logic Controller) which combines PID controller with FLC. In this paper, the output characteristics of CFLC will be compared and analyzed with those PID controller.

One-Chip Microprocessor를 이용한 다변수 Fuzzy Control System의 설계

卓漢浩,金昌圭 진주산업대학교 1993 論文集 Vol.32 No.-

The environment air pollution has becomes worse and go from bad to worse as a result of the industrial growth. There are a lot of factors like dust and smell induce a bad influence on the human body in air. Dusty air is the main factor to bring pulmonary diseases especially. The plenty of cigarette smoke in the airtight office and bad smell in the kitchen not only induce harmful influence upon the human body but also aggravate mental fatigues. Therefore, We absolutely need the any system to keep the air clean. In this paper, we composed multivariable fuzzy control system and programed it to control the air-cleanning system by fuzzy, and simulation results be known to controllable wih the rules, used the 8051 One-chip microprocessor(MICOM) to have the fuzzy functions carried out and the main program for these function is composed of assembler language. We made a board with a emulator for the MICOM part of the fuzzy air-cleanning system, and confirmed the change of controlled quantity according to change of air condition of fan RPM and other various functions through the experiment.